Conclusion

The prediction of urban growth  considering various agents of development with the knowledge of historical land uses through Land use change modeller with the help of Markov- CA. Integration of  temporal remote sensing data with  Geoinformatics are helpful to visualise the urban growth. Incorporation of agents in the modelling exercise provided a realistic picture of the growth. LCM model output validated with the actual data (2012) showed reliability and good accuracy.

Validation of LCM with agents is further used to simulate the land uses by 2020.  The land use scenario show a drastic increase from 24.85 %(2008) to 61.27% (by 2020) with the decline of vegetation and other category. Due to imposing constraint of no-change ion water category, remained constant.  The spatial pattern analysis reveal of concentrated intensified growth at city centre with the increase in urban pockets at suburban, peripheral towns around Bangalore. The city would reach a threshold of urban development by 2020, with the continuation of current approach of urbanisation. This growth would ultimately threaten sustainability of natural resources affecting the livelihood of residents. The trajectory growth is a pointer to the city planners to provision basic amenities apart from conservation of vital natural resources. Land use modelling with the integration of agents (of changes) into   Markov–CA and  with GIS technology has aided in successful simulation of spatial changes and with the reliable forecast. This helps the decision makers in planning sustainable city with the provision of basic infrastructure and amenities. This exercise helps the local land use planners and city administrators with insights to the dynamically evolving complex land use system for conserving the ecological entities and other forms of land uses.